发表机构
RWTH Aachen University（亚琛工业大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
介绍SOLARPROP 2.0，一个开源框架，通过随机微分方程求解输运方程，支持二维和三维磁场模型，并行化加速达三个数量级，并添加Python绑定，经文献验证，多数情况一致，但两个模型存在差异。
AI 中文摘要
我介绍了SOLARPROP的一个大幅改进版本，这是一个用于构建太阳圈中宇宙射线电荷符号依赖太阳调制模型的开源框架。带电粒子的输运方程通过将其转化为一组随机微分方程（SDEs）来求解。该代码现在包含二维空间中的完整SDEs集合，允许具有纬度分量的磁场，并且已推广以适应三维空间中的模型。由于代码并行化和优化，相对于原始版本实现了高达三个数量级的加速。为便于使用，已添加Python绑定。该代码已根据文献中发现的多个模型计算结果进行了验证。虽然在许多情况下发现了一致性极好，但对于两个模型实现观察到了重要差异。已研究了这些差异的可能根本原因。
英文摘要
I present a greatly improved version of SOLARPROP, an open source framework for building models of charge-sign dependent solar modulation of cosmic rays in the heliosphere. The transport equation of charged particles is solved by converting it to a set of stochastic differential equations (SDEs). The code now includes the full set of SDEs in two spatial dimensions, allowing for magnetic fields with latitudinal components, and it has been generalized to accommodate models in three spatial dimensions. Due to code parallelization and optimization, a speedup of up to three orders of magnitude with respect to the original version is achieved. Python bindings have been added for ease of use. The code has been validated against the results of several model calculations found in the literature. While excellent agreement is found in many cases, important differences are observed for two model implementations. Possible root causes for the differences have been investigated.
Comments41 pages, 15 figures, comments welcome, associated source code available at https://github.com/henningrwth/solarprop2
